Date of Award
12-31-2024
Document Type
Dissertation
Degree Name
Doctor of Business Administration (DBA)
Department
School of Business
First Advisor
Paul Shelton, PhD
Second Advisor
Debby Thomas, PhD
Third Advisor
Timothy Veach, PhD
Abstract
Small business acquisition suffers from a lack of information transparency, and many business buyers consequently value acquisitions differently. This project uses the case study methodology to analyze Sound Hardware Inc. and its management team to understand its context in-depth and provide a model that calculates an acquisition price in addition to offering business planning. It does this by using machine learning algorithms to reduce the number of engineered variables resulting in a priority list of factors contributing to value. This core process of dimensionality reduction is followed by a sample valuation that uses the results of the dimensionality reduction in a regression analysis while factoring in management domain knowledge. This results in both a price and a business plan that should match the acquisition phase of company growth to long-term success. The author hopes that this buy-side approach to strategic acquisition planning will be useful to both the academy and to business given its practical nature.
Recommended Citation
Chambers, Jeremy, "Acquisition Targeting: Toward Modelling Small Business Acquisition with Machine Learning" (2024). Doctor of Business Administration (DBA). 72.
https://digitalcommons.georgefox.edu/dbadmin/72